Disorder, Social Control, and Opportunity

.title[
# Disorder, Social Control, and Opportunity
]
.subtitle[
## Advancing research on communities and crime
]
.author[
### Charles C. Lanfear withRoss L. Matsueda & Lindsey R. Beach
]

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# Community Crime Theories

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# Broken Windows

[Wilson & Kelling (1982)](https://www.theatlantic.com/magazine/archive/1982/03/broken-windows/304465/) describe a system where community disorder (1) increases crime by 
signalling low social control to offenders and (2) decreases actual social control by reducing willingness to use public spaces.
--

![Broken Windows](data:image/png;base64,#img/broken_windows_pretty.svg)

]

* B, E: Disorder and crime constrain social relations and impede control.

* C, D: Social control inhibits both disorder and crime.
]

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## Keizer, Lindenberg, & Steg (2008)

Keizer et al. used disorder manipulations and recorded norm violation with field experiments in Groningen, the Netherlands.

Multiple types of disorder consistently increased in norm violation.
--

![Keizer](data:image/png;base64,#img/keizer.svg)

]

* High **internal validity** from experimental design.

* Single sites in one city.
]

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# Collective Efficacy

[Sampson & Raudenbush (1999)](https://doi.org/10.1086/210356) contend that disorder and crime are both manifestations of low collective efficacy—the community's capacity for informal social control.
--

* C, D: Disorder and crime are products of low collective efficacy—social control—which is exogenous (B, E).
]

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## Sampson & Raudenbush (1999)

Simultaneous equations of crime, disorder, and collective efficacy in Chicago neighborhoods, using survey-measured collective efficacy and objectives measure of disorder: Video of block faces coded by researchers.

]

.pull-right[
* Effect of neighborhood disorder on crime (A) absent conditional on collective efficacy (B,D)

* Control for crime impact on collective efficacy (E), but assume no disorder feedback on collective efficacy (absent B).

* High **external validity**: *Real* disorder and crime.
]

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# Today's Talk

Addressing questions raised by these (and related) studies

Bringing methodological concerns to the forefront

Show some key experimental results

Take a glimpse of related work

Chart a path forward for communities research

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class: inverse

# Causality and Counterfactuals

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# Potential Outcomes

Causal effects are differences between *counterfactuals* or *potential outcomes*

Fundamental problem: We only ever see *one* outcome

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# Ignorability

We can compare different units if their differences are *ignorable*

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count: false

# Ignorability

We can compare different units if their differences are *ignorable*

We do this with *randomization* or *conditioning on variables*

* Most prefer randomization because communities are **complex**

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# SUTVA1

* Only one treatment at each measured level
   * No *versions* of treatment
   * No *compound treatments*
* Assignment mechanism for treatment doesn't affect outcomes
]

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# SUTVA1

* Only one treatment at each measured level
   * No *versions* of treatment
   * No *compound treatments*
* Assignment mechanism for treatment doesn't affect outcomes

### No interference

* Unit outcomes are not affected by the treatment assignment of other units
]

---

# Consistency

A mismeasurement: Different types of treatment treated as the same

Commonly violated in field experiments *and* observational research

* e.g., scales combining different treatments1

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## Consistency: Asymmetry

Occurs when treating and removing treatment has different effects

Nearly all studies assume symmetry—but reality is often asymmetric1

* *Pulling the knife out doesn't heal the wound*
* Control conditions may *alter existing states*

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# Interference

Interference means some units' treatments influence other units' outcomes

These spillovers are common in the real world: What happens nearby matters

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# Interference

Interference gets complicated quickly

Can often be ruled out in experiments

* But real processes have spillovers
* Large-scale shocks or policies have unanticipated effects1

.footnote[[1] See [Nagin & Sampson (2019)](https://www.annualreviews.org/doi/abs/10.1146/annurev-criminol-011518-024838)]

---
class: inverse, sncp

# The Seattle Neighborhoods and Crime Project

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## The Experiments

A series of large-scale field experiments embedded in Seattle neighborhoods with rich ecological survey data

* Balance the strengths and weaknesses of experimental and observational methods

&zwj;1. **Mailbox Experiment**

* Effect of disorder on crime / prosocial behavior (replicate Keizer)
* Association between collective efficacy and crime / prosocial behavior

&zwj;2. Lost Letter

&zwj;3. Littering Intervention

&zwj;4. Litter Clean-Up

---

![Experiments](data:image/png;base64,#img/experiments_pretty.svg)

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# Number of Trials

![](data:image/png;base64,#slides_files/figure-html/unnamed-chunk-1-1.svg)

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![](data:image/png;base64,#slides_files/figure-html/unnamed-chunk-2-1.svg)

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# Mailbox: Method

* A letter containing a visible $5 bill is left near mailbox for passersby to encounter.

---

* A letter containing a visible $5 bill is left near mailbox for passersby to encounter.

* Litter and a sign board with graffiti are introduced to manipulate disorder.

* Researchers record whether participants mail, steal, or ignore the envelope.1

.footnote[[1] Perceived gender, age, and group size of participants were also recorded to adjust for compositional differences between conditions]

* Recorded if disorder was present *prior to trial*

* We conducted 368 trials with 3,481 participants in 20 Seattle census tracts.

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# Mailbox: Model

Objective: Causal test of direct effect of disorder on crime (A).

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# Mailbox: Model

Our Experiment: Causal tests of direct effects of disorder on crime and prosocial behavior—and associations with collective efficacy

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# Mailbox: Results

<table style="width:70%">
 <tr>
 <td style="font-size:115%" colspan="5">Mailbox: Participant Actions</td>
 </tr>
 <tr>
 <th>Condition</th>
 <th>Walk-By</th>
 <th>Mail</th>
 <th>Theft</th>
 </tr>
 <tr>
 <td rowspan="2">Control</td>
 <td>1496</td>
 <td>176</td>
 <td>28</td>
 </tr>
 <tr>
 <td>88.0%</td>
 <td>10.4%</td>
 <td>1.6%</td>
 </tr>
 <tr>
 <td rowspan="2">Treatment</td>
 <td>1617</td>
 <td>136</td>
 <td>28</td>
 </tr>
 <tr>
 <td>90.8%</td>
 <td>7.6%</td>
 <td>1.6%</td>
 </tr>
</table>

Key Findings:

* Disorder has **no impact on theft**—Keizer et al. (2008) fails replication1

* Disorder **reduces mailing**

* Thefts higher where **prior disorder** is present, but no difference in treatment effect

* Collective efficacy predicts less **theft** and **prior disorder**

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TRANSITION

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class: inverse

# Recent Projects

* [Lanfear (2022) "Collective efficacy and the built environment" *Criminology*](https://github.com/clanfear/ccl_cv/raw/master/articles/Collective%20Efficacy%20and%20the%20Built%20Environment.pdf)

* Urban political economy, social control, and situational opportunity
   * Modeling long-term, large-scale, endogenous processes

* Lanfear & Matsueda (Ongoing) "A micro theory of crime opportunities:
Symbolic interaction among motivated offenders, suitable targets, and capable
guardians"

* A micro-foundation for situational opportunity and informal control theories

* Lanfear (Ongoing) "Collective efficacy and formal social control"

* The relationship between norms of intervention and police effectiveness

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# Moving Forward

## Survey Research

Strengths of survey but weaknesses: endogeneity; answer with experiments, but  some things difficult to manipulate and external validity an issue; some things not identifiable but not manipulable either---CE -> built environment
    Pitch a 3rd community survey wave in Chicago
    Pitch CE interventions

## Embedded Experiments

## New Data Sources

* Human mobility data

* Space-time budgets

## Multilevel Theory